Triple
T22683178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groruddalen |
E560834
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Groruddalen@no |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Groruddalen@no | Statement: [Groruddalen, hasNameInLanguage, Groruddalen@no]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groruddalen@no Context triple: [Groruddalen, hasNameInLanguage, Groruddalen@no]
-
A.
Groruddalen
chosen
Groruddalen is a large valley and suburban area in the northeastern part of Oslo, Norway, known for its diverse population and extensive residential neighborhoods.
-
B.
Groruddalen area
Groruddalen area is a large valley and suburban region in the northeastern part of Oslo, Norway, known for its diverse residential neighborhoods and significant role in the city's urban development.
-
C.
Drammensdalen
Drammensdalen is a valley in southeastern Norway known for the Drammenselva river and its role as a populated transport corridor between inland areas and the Oslofjord region.
-
D.
Grøtnesdalen
Grøtnesdalen is a small settlement located on the island of Ringvassøya in northern Norway.
-
E.
Nydalen
Nydalen is a modern riverside neighborhood in Oslo, Norway, known for its business district, educational institutions, and redeveloped industrial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1786204d88190a837a5f04e16e94c |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 3:12 p.m.